Last updated 24.08.09

BINFA13647 - Bioinformatics

Program Overview

Major studies: computing, maths, biology, bioinformatics (the integration of computing maths and biology)

Minor Studies: specialist areas in computing, maths and biology such as: biochemistry, molecular biology, statistics, machine learning, algorithms, visualisation, computer interfacing, networks, databases

Professional Recognition: accreditation will be sought from the Institution of Engineers (Australia) and the Australian Computer Society.

Career Opportunities: data analysis and software development in drug companies, biotechnology companies and medical and biological research institutes. Graduates from this course will be also well trained to take up careers in other area of computational data analysis, such as in banks and insurance companies. They could also pursue careers in other more general areas of computing.

Industrial Experience: At least 60 days of approved industrial training must be completed before completion of the final semester. Industrial Training should be concurrent with enrolment and is best accumulated in the summer recesses at the end of years 2 and 3, but must be completed by the end of year 4.

Assumed Knowledge: for Mathematics (MATH1131) - s students will be expected to have achieved the equivalent of a combined mark of at least 100 in HSC Mathematics and HSC Mathematics Extension 1. Failure to meet this required knowledge means that General Mathematics (MATH1011) will have to be taken first. Assumed knowledge for English: at least band 3 in 2 Unit Standard English.

What to Expect 

Bioinformatics is an emerging discipline at the convergence of computing and the life sciences aimed at development of technologies for storing, extracting, organising, analysing, interpreting and utilising the 'tsunami' of information being generated. It is truly an interdisciplinary field. Not only have advances in computing helped accelerate the process of data generation, but the need to process and analyse this vast amount of information has led to advances in both software technologies (databases, algorithm design, machine learning and visualisation) and hardware architectures (IBM's investment in the development of petaflop computers is directly motivated by Bioinformatics problems). Additionally, there is considerable interest in Bioinformatics from researchers in medicine and mathematics.

Bioinformatics graduates receive a bachelor of Engineering after four years. The program is multi-disciplinary and students will achieve a high level of expertise across computing, maths and biology. Students will undertake major project in the fourth year bringing these areas together.

The need for the program

Recent developments in genomics and related disciplines have led to an explosive growth in biological information. Data is being generated faster than it can be analysed and utilised.

The importance of this field to drug discovery has resulted in a rapidly emerging commercial bioinformatics sector. There is a growing niche for professionals with strong foundation in both computing and life Sciences. The current demand is being met either by computing graduates who have to be trained in the necessary domain knowledge or by life science graduates with some informal computing expertise. There is a clear need for a program that educates professionals with expertise in both computing and life sciences and who have learned to integrate these two disciplines.

Program Objectives

Graduates will be able to:

• carry out sophisticated data analysis particularly in the area of biology, which will be to the benefit of society;
• undertake the development of high quality software particularly in the area of data analysis.
• make significant contributions to the development of computing technology, particularly for use in biological data analysis.

Educational principles underpinning the program

• This is a truly interdisciplinary program where principles of computing and life sciences are integrated across the curriculum with foundational concepts from mathematics and statistics.
• The students will be made aware of the context in which the commercial bioinformatics industry is evolving. This will be done from the beginning - 1/3 of the first year course Bioinformatics 1 is devoted to a review of the industry, the profession and the main challenges of the discipline.
• The program will have a strong laboratory focus as a majority of courses have laboratory components aimed at engineering of complex bioinformatics systems.
• The final year thesis adds a capstone research component where students will be able to combine their knowledge of both computing and life sciences to tackle a substantial bioinformatics problem.

Employment after graduation

Potential employers for graduates of these programs include:

• Specialised bioinformatics companies.
• Pharmaceutical and biotech companies employing bioinformatics technology in all stages of the drug discovery process.
• Agbiotech/industrial biotech companies using bioinformatics for study of crops and livestock.
• Computing companies building specialised hardware and software for bioinformatics.

Other potential employers include academic research groups, government agencies such as patent offices and law enforcement agencies.

Many companies within Australia are now looking for Bioinformatics graduates. However, many opportunities to work overseas also exist.

Program Structure

The degree's courses can be roughly broken down to 35% Computing, 35% Biosciences, 15% Maths and 15% specialised Bioinformatics. Each course runs for 12 weeks during session one (S1) or session 2 (S2). UOC denotes Units of Credit, a measure of the amount of work required in a course.

It is recommended that students start thinking about Industrial Training in the summer after Year 2 and Year 3. Graduation may be delayed if a satisfactory report for 60 day industrial training has not been received by the release of final year results.

Electives

Any BIOC/BIOT/MICR/BABS3xxx course for which prerequisites have been completed can be selected as a 3rd year life science elective. Recommended electives include:

Any COMP2xxx or COMP3xxx course for which prerequisites have been completed can be selected as a 3rd year Computing elective. Recommended electives include: 

Alternatively one of the following MATH courses can be chosen instead of a Computing Elective: 

Any Level 3/4/9 COMP course for which prerequistes have been completed can be selected as computing elective. The computing elective can also be replaced by one of the following Mathematics and Statistics course:

General Education 

UNSW wants all students to develop skills in a broad range of areas, not just in their specific study discipline, and so students in all degrees are required to undertake a number of general studies courses outside their discipline. It may not be possible for Bioinformatics Engineering students to enrol in general education courses that are similar in content to the courses offered in the Bioinformatics Engineering degree. For a comprehensive list, see:

http://www.cse.unsw.edu.au/undergrad/current/gened.html

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